Search Results (306)

This study proposes a novel Deep Reinforcement Learning (DRL) policy network structure for portfolio management called PortRSMs. PortRSMs employs stacked State-Space Models (SSMs) for the modeling of multi-scale continuous regime shifts in financial time series, striking a balance between exploring consistent distribution properties over short periods and maintaining sensitivity to sudden shocks in price sequences. PortRSMs also performs cross-asset regime fusion through hypergraph attention mechanisms, providing a more comprehensive state space for describing changes in asset correlations and co-integration. Experiments conducted on two different trading frequencies in the stock markets of the United States and Hong Kong show the superiority of PortRSMs compared to other approaches in terms of profitability, risk–return balancing, robustness, and the ability to handle sudden market shocks. Specifically, PortRSMs achieves up to a 0.03 improvement in the annual Sharpe ratio in the U.S. market, and up to a 0.12 improvement for the Hong Kong market compared to baseline methods. Full article

Container liner shipping companies operate within a complex environment where they must balance profitability and service reliability. Meanwhile, evolving regulatory policies, such as surcharges imposed on ships of a particular origin or type on specific trade lanes, introduce new operational challenges. This study addresses the heterogeneous ship routing and demand acceptance problem, aiming to maximize two conflicting objectives: weekly profit and total transport volume. We formulate the problem as a bi-objective mixed-integer programming model and prove that the ship chartering constraint matrix is totally unimodular, enabling the reformulation of the model into a partially relaxed MIP that preserves optimality while improving computational efficiency. We further analyze key mathematical properties showing that the Pareto frontier consists of a finite union of continuous, piecewise linear segments but is generally non-convex with discontinuities. A case study based on a realistic liner shipping network confirms the model’s effectiveness in capturing the trade-off between profit and transport volume. Sensitivity analyses show that increasing freight rates enables higher profits without large losses in volume. Notably, this paper provides a practical risk management framework for shipping companies to enhance their adaptability under shifting regulatory landscapes. Full article

Global supply chains often face uncertainties in production lead times, fluctuating exchange rates, and varying tariff regulations, all of which can significantly impact total profit. To address these challenges, this study formulates a multi-country supply chain problem as a Semi-Markov Decision Process (SMDP), integrating both currency variability and tariff levels. Using a Q-learning-based method (SMART), we explore three scenarios: (1) wide currency gaps under a uniform tariff, (2) narrowed currency gaps encouraging more local sourcing, and (3) distinct tariff structures that highlight how varying duties can reshape global fulfillment decisions. Beyond these baselines we analyze uncertainty-extended variants and targeted sensitivities (quantity discounts, tariff escalation, and the joint influence of inventory holding costs and tariff costs). Simulation results, accompanied by policy heatmaps and performance metrics, illustrate how small or large shifts in exchange rates and tariffs can alter sourcing strategies, transportation modes, and inventory management. A Deep Q-Network (DQN) is also applied to validate the Q-learning policy, demonstrating alignment with a more advanced neural model for moderate-scale problems. These findings underscore the adaptability of reinforcement learning in guiding practitioners and policymakers, especially under rapidly changing trade environments where exchange rate volatility and incremental tariff changes demand robust, data-driven decision-making. Full article

Indoor horticulture requires a substantial quantity of electricity to meet crops extended photoperiodic requirements for optimal photosynthetic rate. Simultaneously, global electricity costs have grown dramatically in recent years, endangering the sustainability and profitability of indoor vertical farms and/or modern greenhouses that use artificial lighting systems to accelerate crop development and growth. This study investigates the growth rate and physiological development of cherry tomato plants cultivated in a pilot indoor vertical farm at the Agricultural University of Athens’ Laboratory of Farm Structures (AUA) under continuous and disruptive lighting. The leaf physiological traits from multiple photoperiodic stress treatments were analyzed and utilized to estimate the plant’s tolerance rate under varied illumination conditions. Four different photoperiodic treatments were examined and compared, firstly plants grew under 14 h of continuous light (C-14L10D/control), secondly plants grew under a normalized photoperiod of 14 h with intermittent light intervals of 10 min of light followed by 50 min of dark (NI-14L10D/stress), the third treatment where plants grew under 14 h of a load-shifted energy demand response intermittent lighting schedule (LSI-14L10D/stress) and finally plants grew under 13 h photoperiod following of a load-shifted energy demand response intermittent lighting schedule (LSI-13L11D/stress). Plants were subjected also under two different light spectra for all the treatments, specifically WHITE and Blue/Red/Far-red light composition. The aim was to develop flexible, energy-efficient lighting protocols that maintain crop productivity while reducing electricity consumption in indoor settings. Results indicated that short periods of disruptive light did not negatively impact physiological responses, and plants exhibited tolerance to abiotic stress induced by intermittent lighting. Post-harvest data indicated that intermittent lighting regimes maintained or enhanced growth compared to continuous lighting, with spectral composition further influencing productivity. Plants under LSI-14L10D and B/R/FR spectra produced up to 93 g fresh fruit per plant and 30.4 g dry mass, while consuming up to 16 kWh less energy than continuous lighting—highlighting the potential of flexible lighting strategies for improved energy-use efficiency. Full article

Anaerobic digestion (AD) has long been valued for producing a biogas–digestate pair, yet its profitability is tightening. Next-generation AD biorefineries now position syngas both as a supplementary feedstock and as a springboard to capture high-value intermediates, hydrogen (H₂) and volatile fatty acids (VFA). This review dissects how complex natural consortia “decide” between hydrogenogenesis and acetogenesis when CO, H₂, and CO₂ co-exist in the feedstocks, bridging molecular mechanisms with process-scale levers. The map of the bioenergetic contest between the biological water–gas shift reaction and Wood–Ljungdahl pathways is discussed, revealing how electron flow, thermodynamic thresholds, and enzyme inhibition dictate microbial “decision”. Kinetic evidence from pure and mixed cultures is integrated with practical operating factors (gas composition and pressure, pH–temperature spectrum, culture media composition, hydraulic retention time, and cell density), which can bias consortia toward the desired product. Full article

Land Value Capture (LVC) is increasingly being emphasized as a key mechanism for financing mass transit systems, promoted as a sustainability-oriented policy tool amid tightening public budgets. China has adopted a development-led approach to value capture through the “Rail plus Property (R + P)” model, drawing inspiration from the Hong Kong experience. The Shenzhen Metro’s “R + P” strategy has been widely acclaimed as the key to its reputation as “the only profitable transit company in mainland China without subsidies.” This paper questions this assumption and argues that the Shenzhen model is neither sustainable nor replicable, as its past performance depended on two exceptional conditions: an ascending phase of a real-estate cycle and unique institutional concessions from the central state. To substantiate this argument, we contrast Shenzhen’s value capture strategy with that of Nanjing—a provincial capital operating under routine institutional conditions, with governance and spatial structures broadly reflecting the prevailing urban development model in China. Using a comparative framework structured around three key dimensions of LVC—urban governance, risk management, and the transit company’s shift toward real estate—this paper reveals how distinct urban political economies give rise to contrasting value capture approaches: one expansionary, prioritizing short-term profit and rapid scale-up while downplaying risk management (Shenzhen); the other conservative, shaped by institutional constraints and characterized by reactive, incremental adjustments (Nanjing). These findings suggest that while LVC instruments offer valuable potential as a funding source for public transit, their long-term viability depends on early institutional embedding that aligns spatial, fiscal, and political interests, alongside well-developed project planning and capacity support in real estate expertise. Full article

This research investigates the liability management of Thai life insurers in a prolonged low-interest rate environment. It examines the impact of interest rate changes on life insurance products, solvency, and profitability. The study identifies a significant shift in product portfolios toward non-interest-sensitive products, which helps mitigate financial risk and enhance solvency. The solvency of Thai life insurers is influenced by their return on assets, with higher risk exposures requiring more capital, potentially lowering solvency levels. However, the proportion of risky investment assets is not significantly related to the solvency position in the Thai market. The market index return is a significant predictor of stock returns for Thai life insurers, while changes in interest rate sensitivity are not statistically significant between low-rate and normal periods. The average solvency level under Thailand’s regulatory regime is also not statistically different between normal and prolonged low-interest rate situations. This study contributes to the understanding of liability management practices among life insurers in Thailand and provides insights into the challenges and strategies for maintaining solvency and profitability in a low-interest rate environment. Full article

In the context of global e-commerce platform supply chains dominated by Alibaba and Amazon, power reconfiguration among tripartite stakeholders (platforms, manufacturers, and retailers) remains a critical yet underexplored issue in supply chain contract design. To analyze the strategic interactions between platforms, manufacturers, and retailers, as well as how platforms select the contract format within a tripartite supply chain, this study proposes a Stackelberg game-theoretic framework incorporating participation constraints to compare fixed-fee and revenue-sharing contracts. The results demonstrate that revenue-sharing contracts significantly enhance supply chain efficiency by aligning incentives across members, leading to improved pricing and sales outcomes. However, this coordination benefit comes with reduced platform dominance, as revenue-sharing inherently redistributes power toward upstream and downstream partners. The analysis reveals a nuanced contract selection framework: given the revenue sharing rate, as the additional value increases, the optimal contract shifts from the mode RR to the mode RF, and ultimately to the mode FF. Notably, manufacturers and retailers exhibit a consistent preference for revenue-sharing contracts due to their favorable profit alignment properties, regardless of the platform’s value proposition. These findings may contribute to platform operations theory by (1) proposing a dynamic participation framework for contract analysis, (2) exploring value-based thresholds for contract transitions, and (3) examining the power-balancing effects of alternative contract formats. This study offers actionable insights for platform operators seeking to balance control and cooperation in their supply chain relationships, while providing manufacturers and retailers with strategic guidance for contract negotiations in platform-mediated markets. These findings are especially relevant for large e-commerce platforms and their partners managing the complexities of contemporary digital supply chains. Full article

This paper investigates the optimal planning of high-speed rail (HSR) freight operations, pricing strategies, and government carbon tax policies. The primary objective is to enhance the market share of HSR freight, thereby reducing carbon dioxide (CO₂) emissions associated with freight activities. The modal shift problem is formulated as a bi-level multi-objective model and solved using a specifically designed hybrid algorithm. The upper-level model integrates multiple objectives of the government (minimizing tax while maximizing the emission reduction rate) and HSR operators (maximizing profits). The lower-level model represents shippers’ transportation mode choices through network equilibrium modeling, aiming to minimize their costs. Numerical analysis is conducted using a transportation network that includes seven major central cities in China. The results indicate that optimizing HSR freight services with carbon tax policies can achieve a 56.97% reduction in CO₂ emissions compared to air freight only. The effectiveness of the government’s carbon tax policy in reducing CO₂ emissions depends on shippers’ emphasis on carbon reduction and the intensity of the carbon tax. Full article

In recent years, online retailing platforms (ORPs) have increasingly introduced private brand (PB) products as a new profit source, reshaping market dynamics and affecting their commission revenues. This shift creates a strategic trade-off for the platform: maximizing PB product profits while maintaining commission income from national brand (NB) retailers. This paper examines the platform’s pricing and quality strategies for PB products, as well as its incentives to introduce them. We develop a game-theoretic model featuring a platform and a retailer, and derive results through equilibrium analysis and comparative statics. Special attention is given to the platform’s strategy when market power is asymmetric and the PB product is homogeneous. The analysis yields three key findings. Firstly, the platform is always incentivized to introduce a PB product, regardless of its brand value. Even when direct profit is limited, the platform can leverage the PB product to increase competitive pressure on the retailer and boost commission revenue. Secondly, when the PB product has low brand value, the platform adopts a cost-saving strategy with low quality for extremely low brand value, and a function-enhancing strategy with high quality for moderately low brand value. Thirdly, when the PB product has high brand value, the platform consistently prefers a function-enhancing strategy. This study contributes to the literature by systematically characterizing the platform’s strategic trade-offs in introducing PB products, highlighting its varied pricing and quality strategies across categories, and revealing the critical role of brand value in supply chain competition. Full article

Given the increasing energy demand and the environmental consequences of fossil fuel consumption, the shift toward sustainable energy sources has become a global priority. Renewable Energy Communities (RECs)—comprising citizens, businesses, and legal entities—are emerging to democratise access to renewable energy. These communities allow members to produce their own energy, sharing or selling any surplus, thus promoting sustainability and generating economic value. However, scaling RECs while ensuring profitability is challenging due to renewable energy intermittency, price volatility, and heterogeneous consumption patterns. To address these issues, this paper presents a Machine Learning as a Service (MLaaS) framework, where each REC microgrid has a customised Reinforcement Learning (RL) agent and electricity price forecasts are included to support decision-making. All the conducted experiments, using the open-source simulator Pymgrid, demonstrate that the proposed agents reduced operational costs by up to 96.41% compared to a robust baseline heuristic. Moreover, this study also introduces two cost-saving features: Peer-to-Peer (P2P) energy trading between communities and internal energy pools, allowing microgrids to draw local energy before using the main grid. Combined with the best-performing agents, these features achieved trading cost reductions of up to 45.58%. Finally, in terms of deployment, the system relies on an MLOps-compliant infrastructure that enables parallel training pipelines and an autoscalable inference service. Overall, this work provides significant contributions to energy management, fostering the development of more sustainable, efficient, and cost-effective solutions. Full article

Background/Objectives: Community benefit (CB) obligations by not-for-profit (NFP) hospitals have attracted renewed scrutiny at federal and state levels due to wide variation in CB spending. In 2020, Oregon implemented a CB policy for all NFP hospitals that included requirements to expand patient financial assistance and a hospital-specific minimum CB spending floor. We examined trends in CB spending after the implementation of Oregon’s CB policy. Methods: Interrupted time-series analyses to compare hospital CB spending before and after policy implementation. Results: Overall, Oregon’s CB policy was not associated with changes in CB spending, except for a 0.2% decrease in the Social Determinants of Health spending (−0.0018; p < 0.05). Among hospitals in the first tercile of pre-policy CB spending, Oregon’s policy was associated with a 0.4% decrease in charity care (−0.0041; p < 0.05) and a 0.6% increase in subsidized health services spending (0.0063; p < 0.05). Hospitals in the second tercile of pre-policy CB spending experienced a 0.7% decrease in subsidized health services (−0.0074; p < 0.05). Among frontier hospitals, total CB spending and Medicaid shortfalls increased by 2.9% (0.0292; p < 0.10) and 2.2% (0.0220; p < 0.10) respectively, while non-frontier hospitals experienced a 0.7% decrease in Medicaid shortfall (−0.0068; p < 0.05). Critical access hospitals experienced a 1.3% increase in subsidized health services spending (0.0131; p < 0.05). Conclusions: Although total CB spending did not change in the two years following Oregon’s CB policy implementation, findings suggest that hospitals may be shifting the composition of their CB spending. Oregon’s CB policy encourages proactive CB spending tailored to community needs, but opportunities exist to fine-tune the policy to boost hospital CB spending. Specifically, planned spending in categories such as charity care may alleviate the increasing burden of medical debt and its financial implications for patients. Full article

The primary objective of this study is to investigate the intricate relationship between different ownership structures, such as family, institutional, managerial, and foreign ownership, and tax avoidance practices. It also seeks to explore the moderating influence of female board members in shaping these relationships. This study utilizes balanced panel data from 72 industrial and service firms listed on the Amman Stock Exchange during the period of 2018 to 2023. The Generalized Method of Moments (GMM) was employed to estimate the results. The results indicate that family and foreign ownership positively influence tax avoidance practices, suggesting that families may engage in tax avoidance to benefit from rent extraction, while foreign investors may pressure managers to manipulate tax liabilities or shift profits across countries to minimize taxes. In contrast, the presence of female directors as well as institutional and managerial ownership is associated with a reduction in tax avoidance. Female directors play a moderating role in the relationship between ownership structure and tax avoidance. Their presence in interaction with institutional ownership reduces tax avoidance by focusing on tax compliance strategies. However, this effect changes in family and foreign-owned firms, where control over decision-making lies with the families or foreign shareholders, limiting the impact of female directors in promoting compliance and aligning their role with the tax avoidance strategies preferred by the controlling owners. Full article

The research explores three interconnected themes: philosophy, education, and ecology. It aims to be an interdisciplinary study that emphasizes the significance of the philosophy of environmental education and its practical implications. Initially, it addresses the contemporary hylomorphic production approach, followed by proposing educational solutions aimed at fostering a comprehensive understanding of the environment. This understanding includes recognizing humans as part of the environment, sharing equal rights to existence with all other life forms. The study advocates for a shift away from anthropocentrism, positioning humans in a non-privileged role within the ecosystem. It seeks to challenge long-standing notions where humans have historically placed themselves above other beings. The research is particularly inspired by the “Green Schools” in Bali, which embody a proactive educational philosophy aimed at reshaping how future generations perceive their role in production and environmental stewardship. These schools promote an educational framework that encourages students to reconnect with nature and develop sustainable practices from the ground up, moving away from exploitative and profit-driven paradigms. An example of this innovative approach is found in disciplines such as “eco-art,” where colors are derived from natural relationships rather than manufactured. The overarching goal is to cultivate a perspective that sees humans as integral components of nature, valuing it for its intrinsic worth rather than solely for its utility to humanity. Full article

A company’s base, or physical location, is often a criterion or condition for inclusion in regional development programmes that offer investment incentives such as reduced taxes, subsidised loan rates, or funding for research and development projects. However, these programmes, aimed at strengthening communities lagging behind in economic development, are often the target of malicious exploitation by companies that have a virtual headquarters in the region without actually contributing to local economies. This study proposes the use of the Expenses Localness Indicators (ELI) model as a reliable indicator of a company’s real contribution to a local economy. The ELI model can measure and highlight attempts to erode a company’s headquarters, and also assess a company’s integration into the local economy. By simulating a virtual economic environment and generating synthetic transaction data, the effectiveness of the ELI model in detecting false location claims and quantifying regional participation is evaluated. The results show that companies that prioritise local partnerships maintain higher locality scores, while those that partner with low locality entities weaken their local economic footprint, regardless of physical location. The ELI model provides a transparent and reliable tool that can be used both to grant regional incentives and to monitor their performance. Its integration into policy design can support more equitable, evidence-based approaches to regional economic development and social investment. Full article